Author of

• 15934

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  MINI 32 - Topics in Localized Lung Cancer (ID 166)

  • Event: WCLC 2015
  • Type: Mini Oral
  • Track: Treatment of Localized Disease - NSCLC
  • Presentations: 1
  • Moderators:D. Boffa, T. D'Amico
  • Coordinates: 9/09/2015, 18:30 - 20:00, 201+203

  • 15942

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    MINI32.08 - Identification of a Meta-Gene Network Associated with Metformin Sensitivity and Recurrence in Stage I Non-Small Cell Lung Cancer (ID 1727)

    19:10 - 19:15  |  Author(s): C.A. Frankenberger
    • Abstract
    • Presentation
    • Slides

    Background:
    We recently reported an association between progression-free survival and metformin exposure in patients with early stage non-small cell lung cancer (NSCLC). Local recurrence in stage I disease is estimated to be as high as 50% in US populations. Therefore, a method to identify NSCLC patients who are most likely to benefit from metformin treatment has potential clinical relevance.
    
    Methods:
    Three previously published, publically available gene expression array data sets documenting the effects of metformin treatment on transcriptional activity in human cell lines were used for the initial stages of the present study. These data sets were evaluated individually for enrichment of differentially expressed genes with a gene set analysis related to biological processes also performed. Differentially expressed genes common to all three studies were then used to form a metformin meta-gene. This combined meta-gene was evaluated topologically using a protein-protein interaction database to determine if any gene products had previously observed direct interactions. The metformin meta-gene network was then examined in expression array data sets from stage I NSCLC patients (n=293) assembled from multiple published studies.
    
    Results:
    We identified several biological themes resulting from metformin treatment, including: immune cell differentiation, response to hypoxia, steroid receptor signaling, alternate splicing, and changes in cellular metabolism. Intersecting the differentially expressed genes from each data set, we identified 105 genes consistently up-regulated and 30 genes consistently down-regulated by metformin treatment, forming a tissue-independent meta-gene for metformin effects. Two networks of interacting genes were identified in this analysis; the first network consisting of 27 genes (22 up-regulated and 5 down-regulated) and the second consisting of three up-regulated genes.This meta-gene was then examined in two independent cohorts of stage I adenocarcinoma. In the first cohort (n=125), patients clustered into two groups when k-means analysis was performed with respect to the 30 genes in the metformin meta-gene network. These patients had a significantly (p=0.014) different incidence of recurrence between the two clusters. This result was independently validated in the second data set (n=168) where patients clustered into two groups and also demonstrated significant stratification of recurrence (HR=1.21; p=0.001).
    
    Conclusion:
    We have identified a meta-gene of interacting proteins associated with both metformin therapy and recurrence-free survival in early stage lung cancer patients. This suggests a potential method for identifying NSCLC patients most likely to benefit from metformin therapy, and furthermore, identifies mechanistic avenues by which metformin treatment may benefit early stage lung cancer patients.
    
    

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